R/ion_bar_plot.R

In EMSL-Computing/pspecterlib: PSpecteR Library - Visualization tools for top-down and bottom-up proteomics data

#' Make a bar plot of fragments per ion
#'
#' @description Generates a bar plot of counts of all fragments, fragments without
#'    isotopes, and fragments with unique charge states per ion.
#'
#' @param MatchedPeaks Object of the matched_peaks class from get_matched_peaks. Default is NULL. Required.
#' @param Interactive A logical to determine whether the plot should be interactive or not. Default is FALSE.
#'
#' @examples
#' \dontrun{
#'
#' # Test with bottom up data
#' BU_Peak <- get_peak_data(ScanMetadata = BU_ScanMetadata, ScanNumber = 31728)
#' BU_Match <- get_matched_peaks(ScanMetadata = BU_ScanMetadata, PeakData = BU_Peak)
#'
#' # Make the plot interactive or not
#' ion_bar_plot(MatchedPeaks = BU_Match)
#' ion_bar_plot(MatchedPeaks = BU_Match, Interactive = TRUE)
#'
#' }
#'
#' @export
ion_bar_plot <- function(MatchedPeaks,
                         Interactive = FALSE) {


  ##################
  ## CHECK INPUTS ##
  ##################

  # Assert that Matched Peaks is of the correct type
  if (is.null(MatchedPeaks) == FALSE && "matched_peaks" %in% class(MatchedPeaks) == FALSE) {
    stop("MatchedPeaks must be of the class matched_peaks generated by get_matched_peaks.")
  }

  # Assert that Interactive is a single logical
  if (is.logical(Interactive) == FALSE || length(Interactive) > 1) {
    stop("Interactive must be a single logical value TRUE or FALSE.")
  }
  if (is.na(Interactive)) {
    Interactive <- FALSE
  }

  ############################
  ## DEFINE LOCAL FUNCTIONS ##
  ############################

  countBar <- function(vector) {
    counts <- vector %>% table() %>% data.frame()
    colnames(counts) <- c("Ion", "Count")
    counts <- rbind(counts, data.frame("Ion" = "Total", "Count" = sum(counts$Count)))
    return(counts)
  }

  #############################
  ## GENERATE PLOT DATAFRAME ##
  #############################

  # Get MatchedPeaks object
  class(MatchedPeaks) <- "data.frame"

  # Count All Ions
  IonsAll <- countBar(MatchedPeaks$Type)

  # Count Ions Exluding Isotopes
  IonsNoIso <- MatchedPeaks %>% subset(Isotope == "M") %>% dplyr::select(Type) %>% countBar()

  # Count Unique Ions Per Fragment
  IonsUnique <- MatchedPeaks %>% dplyr::select(Ion, Type) %>% unique() %>% dplyr::select(Type) %>% countBar()

  # Generate plotting dataframe
  BarplotDF <- cbind("Method" = c(rep("All Ions", nrow(IonsAll)),
                                  rep("Ions without Isotopes", nrow(IonsNoIso)),
                                  rep("Unique ions per fragment", nrow(IonsUnique))),
                     rbind(IonsAll, IonsNoIso, IonsUnique)) %>% data.frame()

  ###############
  ## MAKE PLOT ##
  ###############

  # Generate the plot
  BarPlot <- ggplot2::ggplot(BarplotDF, ggplot2::aes(x = Ion, y = Count, fill = Method)) +
    ggplot2::geom_bar(stat = "identity",  position = ggplot2::position_dodge(), color = "black") +
    ggplot2::theme_bw() + ggplot2::scale_fill_brewer(palette = "greens")

  # Return interactive if TRUE
  if (Interactive) {
    return(BarPlot %>% plotly::ggplotly())
  } else {return(BarPlot)}

}